Monday, March 31, 2014

A new paper published in Nature Communications finds a "clear correlation" between solar and volcanic activity and a 5-year lagged response of the Atlantic Multidecadal Oscillation [AMO] over the past 250 years, which in turn drives the climate of the Northern Hemisphere. This may represent yet another solar amplification mechanism by which tiny variations in solar activity have large-scale effects on climate.

According to the paper, "The results actually showed that during the last approximately 250 years -- since the period known as the Little Ice Age -- a clear correlation can be seen where the external forces, i.e. the Sun's energy cycle and the impact of volcanic eruptions, are accompanied by a corresponding temperature fluctuation with a time lag of about five years."

"This phenomenon is called the Atlantic Multidecadal Oscillation (AMO), which consists of relatively warm periods lasting thirty to forty years being replaced by cool periods of the same duration. The researchers were able to read small systematic variations in the water temperature in the North Atlantic in measurements taken by ships during the last 140 years."

"Although the temperature fluctuations are small -- less than 1°C -- there is a general consensus among climate researchers that the AMO phenomenon has had a major impact on the climate in the area around the North Atlantic for thousands of years, but until now there has been doubt about what could cause this slow rhythm in the temperature of the Atlantic Ocean."

"Another model explains the AMO as being driven by fluctuations in the amount of solar energy received by the Earth, and as being affected by small changes in the energy radiated by the Sun itself and the after-effects of volcanic eruptions. Both these factors are also known as 'external forces' that have an impact on the Earth's radiation balance."

"However, there has been considerable scepticism towards the idea that a phenomenon such as an AMO could be driven by external forces at all -- a scepticism that the Aarhus researchers now demonstrate as unfounded"

"It should also be pointed out that these fluctuations occur on the basis of evenly increasing ocean temperatures during the last approximately fifty years -- an increase connected with global warming,"

"During the last century, the AMO has had a strong bearing on significant weather phenomena such as hurricane frequency and droughts -- with considerable economic and human consequences. A better understanding of this phenomenon is therefore an important step for efforts to deal with and mitigate the impact of climate variations,"

"The results provide a new and very important perspective on the AMO phenomenon because they are based on data and not computer models, which are inherently incomplete. The problem is that the models do not completely describe all the physical correlations and feedbacks in the system, partly because these are not fully understood. And when the models are thus unable to reproduce the actual AMO signal, it is hard to know whether they have captured the essence of the AMO phenomenon."

"An interesting new theory among solar researchers and meteorologists is that the Sun can control climate variations via the very large variations in UV radiation, which are partly seen in connection with changes in sunspot activity during the Sun's eleven-year cycle. UV radiation heats the stratosphere in particular via increased production of ozone, which can have an impact on wind systems and thereby indirectly on the global ocean currents as well,"

Natural fluctuations in the ocean temperature in the North Atlantic have a significant impact on the climate in the northern hemisphere. These fluctuations are the result of a complex dance between the forces of nature, but researchers can now show that solar activity and the impact of volcanic eruptions have led this dance during the last two centuries.

Ocean temperature has been regularly measured since 1870, which makes it possible to calculate a mean temperature at each point for the period for the period 1870 to the present day. Ocean temperature varies throughout the year and there are significant variations due to weather systems and over longer timescales. These illustrations show how the average temperatures over 20-year intervals have varied between cold (blue) and warm (red) periods. This variation is called the Atlantic Multidecadal Oscillation, abbreviated to AMO.

Imagine a ballroom in which two dancers apparently keep in time to their own individual rhythm. The two partners suddenly find themselves moving to the same rhythm and, after a closer look, it is clear to see which one is leading.

It was an image like this that researchers at Aarhus University were able to see when they compared studies of solar energy release and volcanic activity during the last 450 years, with reconstructions of ocean temperature fluctuations during the same period.

The results actually showed that during the last approximately 250 years -- since the period known as the Little Ice Age -- a clear correlation can be seen where the external forces, i.e. the Sun's energy cycle and the impact of volcanic eruptions, are accompanied by a corresponding temperature fluctuation with a time lag of about five years.

In the previous two centuries, i.e. during the Little Ice Age, the link was not as strong, and the temperature of the Atlantic Ocean appears to have followed its own rhythm to a greater extent.

The results were recently published in the scientific journal Nature Communications.

In addition to filling in yet another piece of the puzzle associated with understanding the complex interaction of the natural forces that control the climate, the Danish researchers paved the way for linking the two competing interpretations of the origin of the oscillation phenomenon.Temperature fluctuations discovered around the turn of the millennium

The climate is defined on the basis of data including mean temperature values recorded over a period of thirty years. Northern Europe thus has a warm and humid climate compared with other regions on the same latitudes. This is due to the North Atlantic Drift (often referred to as the Gulf Stream), an ocean current that transports relatively warm water from the south-west part of the North Atlantic to the sea off the coast of Northern Europe.

Around the turn of the millennium, however, climate researchers became aware that the average temperature of the Atlantic Ocean was not entirely stable, but actually fluctuated at the same rate throughout the North Atlantic. This phenomenon is called the Atlantic Multidecadal Oscillation (AMO), which consists of relatively warm periods lasting thirty to forty years being replaced by cool periods of the same duration. The researchers were able to read small systematic variations in the water temperature in the North Atlantic in measurements taken by ships during the last 140 years.

Although the temperature fluctuations are small -- less than 1°C -- there is a general consensus among climate researchers that the AMO phenomenon has had a major impact on the climate in the area around the North Atlantic for thousands of years, but until now there has been doubt about what could cause this slow rhythm in the temperature of the Atlantic Ocean. One model explains the phenomenon as internal variability in the ocean circulation -- somewhat like a bathtub sloshing water around in its own rhythm. Another model explains the AMO as being driven by fluctuations in the amount of solar energy received by the Earth, and as being affected by small changes in the energy radiated by the Sun itself and the after-effects of volcanic eruptions. Both these factors are also known as 'external forces' that have an impact on the Earth's radiation balance.

However, there has been considerable scepticism towards the idea that a phenomenon such as an AMO could be driven by external forces at all -- a scepticism that the Aarhus researchers now demonstrate as unfounded

"Our new investigations clearly show that, since the Little Ice Age, there has been a correlation between the known external forces and the temperature fluctuations in the ocean that help control our climate. At the same time, however, the results also show that this can't be the only driving force behind the AMO, and the explanation must therefore be found in a complex interaction between a number of mechanisms. It should also be pointed out that these fluctuations occur on the basis of evenly increasing ocean temperatures during the last approximately fifty years -- an increase connected with global warming," says Associate Professor Mads Faurschou Knudsen, Department of Geoscience, Aarhus University, who is the main author of the article.

Convincing data from the Earth's own archives

Researchers have attempted to make computer simulations of the phenomenon ever since the discovery of the AMO, partly to enable a better understanding of the underlying mechanism. However, it is difficult for the computer models to reproduce the actual AMO signal that can be read in the temperature data from the last 140 years.

Associate Professor Knudsen and his colleagues instead combined all available data from the Earth's own archives, i.e. previous studies of items such as radioactive isotopes and volcanic ash in ice cores. This provides information about solar energy release and volcanic activity during the last 450 years, and the researchers compared the data with reconstructions of the AMO's temperature rhythm during the same period.

"We've only got direct measurements of the Atlantic Ocean temperature for the last 140 years, where it was measured by ships. But how do you measure the water temperature further back in time? Studies of growth rings in trees from the entire North Atlantic region come into the picture here, where 'good' and 'bad' growth conditions are calibrated to the actual measurements, and the growth rings from trees along the coasts further back in time can therefore act as reserve thermometers," explains Associate Professor Knudsen.

The results provide a new and very important perspective on the AMO phenomenon because they are based on data and not computer models, which are inherently incomplete. The problem is that the models do not completely describe all the physical correlations and feedbacks in the system, partly because these are not fully understood. And when the models are thus unable to reproduce the actual AMO signal, it is hard to know whether they have captured the essence of the AMO phenomenon.

Impact of the sun and volcanoes

An attempt to simply explain how external forces such as the Sun and volcanoes can control the climate could sound like this: a stronger Sun heats up the ocean, while the ash from volcanic eruptions shields the Sun and cools down the ocean. However, it is hardly as simple as that.

"Fluctuations in ocean temperature have a time lag of about five years in relation to the peaks we can read in the external forces. However, the direct effect of major volcanic eruptions is clearly seen as early as the same year in the mean global atmospheric temperature, i.e. a much shorter delay. The effect we studied is more complex, and it takes time for this effect to spread to the ocean currents," explains Associate Professor Knudsen.

"An interesting new theory among solar researchers and meteorologists is that the Sun can control climate variations via the very large variations in UV radiation, which are partly seen in connection with changes in sunspot activity during the Sun's eleven-year cycle. UV radiation heats the stratosphere in particular via increased production of ozone, which can have an impact on wind systems and thereby indirectly on the global ocean currents as well," says Associate Professor Knudsen. However, he emphasises that researchers have not yet completely understood how a development in the stratosphere can affect the ocean currents on Earth.

Towards a better understanding of the climate

"In our previous study of the climate in the North Atlantic region during the last 8,000 years, we were able to show that the temperature of the Atlantic Ocean was presumably not controlled by the Sun's activity. Here the temperature fluctuated in its own rhythm for long intervals, with warm and cold periods lasting 25-35 years. The prevailing pattern was that this climate fluctuation in the ocean was approximately 30-40% faster than the fluctuation we'd previously observed in solar activity, which lasted about ninety years. What we can now see is that the Atlantic Ocean would like to -- or possibly even prefer to -- dance alone. However, under certain circumstances, the external forces interrupt the ocean's own rhythm and take over the lead, which has been the case during the last 250 years," says Associate Professor Bo Holm Jacobsen, Department of Geoscience, Aarhus University, who is the co-author of the article.

"It'll be interesting to see how long the Atlantic Ocean allows itself to be led in this dance. The scientific challenge partly lies in understanding the overall conditions under which the AMO phenomenon is sensitive to fluctuations in solar activity and volcanic eruptions," he continues.

"During the last century, the AMO has had a strong bearing on significant weather phenomena such as hurricane frequency and droughts -- with considerable economic and human consequences. A better understanding of this phenomenon is therefore an important step for efforts to deal with and mitigate the impact of climate variations," Associate Professor Knudsen concludes.

Story Source:

The above story is based on materials provided by Aarhus University. The original article was written by Christina Troelsen. Note: Materials may be edited for content and length.

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Abstract

The Atlantic Multidecadal Oscillation (AMO) represents a significant driver of Northern Hemisphere climate, but the forcing mechanisms pacing the AMO remain poorly understood. Here we use the available proxy records to investigate the influence of solar and volcanic forcing on the AMO over the last ~450 years. The evidence suggests that external forcing played a dominant role in pacing the AMO after termination of the Little Ice Age (LIA; ca. 1400–1800), with an instantaneous impact on mid-latitude sea-surface temperatures that spread across the North Atlantic over the ensuing ~5 years. In contrast, the role of external forcing was more ambiguous during the LIA. Our study further suggests that the Atlantic Meridional Overturning Circulation is important for linking external forcing [the Sun] with North Atlantic sea-surface temperatures, a conjecture that reconciles two opposing theories concerning the origin of the AMO.

A paper published today in Nature Climate Change attempts to revive the Gergis et al zombie hockey stick, but as Steve McIntyre and others have already observed, the paper is a reworking of a previously discredited paper, and is "non-compliant with [anti-data-torturing] protocols on several important counts, including its unprecedented ex-post screening [only using proxies that show a hockey stick shape, rejecting non-hockey-sticks] and its reliance on the same proxies that have been used in multiple previous studies."Even if one believes this highly-flawed paper that selects only hockey-stick proxies, the proxy reconstruction of Northern Hemisphere temperatures shown in Fig 2a below indicate only a small ~0.25C difference between the Medieval Warm Period temperatures ~1000 years ago and temperatures at the end of the record in 2000. The Southern Hemisphere reconstruction shows almost no difference in temperature between the MWP peak and the year 2000. In addition, Figure 2a shows Northern Hemisphere temperatures not statistically-significantly different between the early 1300's [at the beginning of the Little Ice Age] and the year 2000.

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The Earth’s climate system is driven by a complex interplay of internal chaotic dynamics and natural and anthropogenic external forcing. Recent instrumental data have shown a remarkable degree of asynchronicity between Northern Hemisphere and Southern Hemisphere temperature fluctuations, thereby questioning the relative importance of internal versus external drivers of past as well as future climate variability1, 2, 3. However, large-scale temperature reconstructions for the past millennium have focused on the Northern Hemisphere4, 5, limiting empirical assessments of inter-hemispheric variability on multi-decadal to centennial timescales. Here, we introduce a new millennial ensemble reconstruction of annually resolved temperature variations for the Southern Hemisphere based on an unprecedented network of terrestrial and oceanic palaeoclimate proxy records. In conjunction with an independent Northern Hemisphere temperature reconstruction ensemble5, this record reveals an extended cold period (1594–1677) in both hemispheres but no globally coherent warm phase during the pre-industrial (1000–1850) era. The current (post-1974) warm phase is the only period of the past millennium where both hemispheres are likely to have experienced contemporaneous warm extremes. Our analysis of inter-hemispheric temperature variability in an ensemble of climate model simulations for the past millennium suggests that models tend to overemphasize Northern Hemisphere–Southern Hemisphere synchronicity by underestimating the role of internal ocean–atmosphere dynamics, particularly in the ocean-dominated Southern Hemisphere. Our results imply that climate system predictability on decadal to century timescales may be lower than expected based on assessments of external climate forcing and Northern Hemisphere temperature variations5, 6 alone.

From over 25 hemispheric-scale temperature reconstructions published in recent decades, only three cover the ocean-dominated Southern Hemisphere7. These Southern Hemisphere temperature reconstructions include only seven8 or fewer9 proxy datasets for the entire Southern Hemisphere, or were provided as peripheral components of Northern Hemisphere and global reconstruction efforts4 with the caveat that ‘more confident statements about long-term temperature variations in the Southern Hemisphere and globe on the whole must await additional proxy data collection’4. Consequently, attribution of temperature changes to external forcings10, 11 and investigations of the coupling between temperature and greenhouse gas concentrations5, 6 have focused on the Northern Hemisphere.

Data spanning inter-annual to multi-millennial timescales suggest limited temperature coherence between the two hemispheres. The degree of independence in Northern Hemisphere and Southern Hemisphere temperature trends over the past 150 years2 indicates that responses to external forcing may be modulated by ocean–atmosphere variability, reducing predictability of the climate system in twenty-first century model projections1, 3. Patterns of late Quaternary deglaciation have also demonstrated high inter-hemispheric variability, attributed to a coupling of orbital forcing, ice-albedo feedbacks and the Atlantic Meridional Overturning Circulation12, 13. Finally, a recent evaluation of multi-centennial reconstructions from seven continents also suggests stronger regional temperature coherence within the hemispheres than between them14. Yet, the preliminary nature of existing annually resolved Southern Hemisphere temperature reconstructions has hindered knowledge of the existence and driving mechanisms of inter-hemispheric climate variability on the societally relevant multi-decadal to centennial timescales.

Here, we introduce a Southern Hemisphere temperature reconstruction ensemble and assess inter-hemispheric temperature variability over the past millennium in both empirical reconstructions and state-of-the-art climate model simulations. We use an extensive Southern Hemisphere palaeoclimate data network from more than 300 individual sites15 yielding 111 temperature predictors (Supplementary Section 1). This proxy collection nearly doubles the number of records considered in the most advanced previous reconstruction attempt4, now allowing the development of an annually resolved and well-verified Southern Hemisphere temperature reconstruction for the past millennium (Fig. 1 and Supplementary Section 2) which is insensitive to moderate changes in reconstruction methodology or proxy network composition (Supplementary Section 3).

Figure 1: Proxy data and calibration performance.

a, Southern Hemisphere temperature reconstruction proxies. Shading represents GISS instrumental grid-cell temperature28 correlations in the period 1911–1990, with the Southern Hemisphere field mean used as reconstruction target (all data linearly detrended). Cells with less than 30 years of data are blank. b, Temporal evolution of the number of proxy time series used in the reconstruction, with colours indicating the relative contribution of each archive and calibration (red) and verification (green) RE skill metric for the period 1000–2000. c, Instrumental target temperatures (with respect to 1961–1990) over the 1911–1990 calibration/verification period (black) and reconstruction ensemble means of the years used for calibration (red) and verification (green) for the most replicated proxy nest. Details in Methods and Supplementary Section 3.1.3.

Although our database is weighted towards the Pacific sector of the Southern Hemisphere (Fig. 1a), the proxy network captures the inter-annual to long-term variability in Southern Hemisphere mean temperatures recorded by instrumental data (calibration: r = 0.73–0.95, RE = 0.50–0.91; verification: r = 0.57–0.88, RE = 0.32–0.77; all p 0.01; Fig. 1b, c). The Southern Hemisphere reconstruction ensemble shows temperatures in the period 1000 to 1200 CE (all years hereafter Common Era) that are close to the long term (1000–2000) average. This is followed by an approximately 150-year warm phase (1200–1350) containing the warmest pre-industrial temperatures of the past millenium (Fig. 2a). The subsequent long-term cooling trend reaches a minimum around 1600, with negative decadal-scale ensemble-mean temperature anomalies prevailing until the early twentieth century. 99.7% of the Southern Hemisphere reconstruction ensemble members indicate that the late twentieth century contained the warmest decade of the past millennium. This finding complements well-established evidence for the anomalous characteristics of Northern Hemisphere industrial-era warming5. Besides the positive twentieth century temperature anomalies, simultaneous cold anomalies in both hemispheres are identified between 1571 and 1722 (based on the 1000–2000 long term mean; Fig. 2a). During the rest of the millennium, the Northern Hemisphere and Southern Hemisphere are more prominently characterized by differences in the occurrence, timing and phase of warm and cold episodes. In medieval times, Southern Hemisphere temperature anomalies are notably colder than the Northern Hemisphere both before 1100 and around 1400, and warmer between 1280 and 1350. Expression of the industrial-era warming trend in the Southern Hemisphere also lags by approximately 25 years behind the Northern Hemisphere. Moreover, Southern Hemisphere temperatures tend to show a weaker cooling response to strong volcanic eruptions, for example, during the early nineteenth century.

Figure 2: Temperature variability over the past millennium.

a, 30-year loess filtered ensemble mean temperature reconstruction for the Southern Hemisphere (SH; blue) and Northern Hemisphere (NH; red) relative to the millennium mean for the period 1000–2000. Blue shading based on Southern Hemisphere reconstruction uncertainties (Supplementary Section 2.4). Thin orange lines represent the ensemble means of the nine individual temperature reconstructions making up the Northern Hemisphere dataset5. b, as a but for the 24-member climate model ensemble. Note for consistency with reconstruction data, simulated temperatures are shown as individual simulations for the Northern Hemisphere and a probabilistic range based on ensemble percentiles for the Southern Hemisphere.

To determine the extent to which reconstructed temperature patterns are independently identified by climate models, we investigate inter-hemispheric temperature coherence from a 24-member multi-model ensemble (simulation details in Supplementary Table 9). Very similar temperature evolutions are modelled for the two hemispheres (Fig. 2b). The majority of model ensemble members show warmest pre-industrial temperatures sometime between 1050 and 1250 in the Northern Hemisphere (79% of ensemble members), the Southern Hemisphere (75%), and simultaneously in both (67%) hemispheres. Interestingly, this simulated warm period is delayed compared to the reconstructed medieval warmth in the Northern Hemisphere and precedes the phase of maximum Southern Hemisphere pre-industrial warmth16. Between 1300 and 1900, simulated temperatures are close to the 1000–2000 average, periodically interrupted by shorter volcanically induced cold excursions. In contrast to the delay in industrial Southern Hemisphere warming in the reconstructions, the climate model simulations show a mostly synchronous temperature increase after 1850. Mean correlations between 30-year filtered reconstructions and simulations for all possible ensemble pairs are r = 0.29 ± 0.22 (2σ ensemble spread) for the Southern Hemisphere and r = 0.47 ± 0.33 for the Northern Hemisphere. These values increase to r= 0.35 and r = 0.77 for the ensemble means. As the model ensemble means are subjected less to internal variability than each individual simulation and better represent the temperature response to external forcing, these values suggest substantially weaker links between external forcing and Southern Hemisphere temperature variability compared to the Northern Hemisphere.

We quantify coherence between Northern Hemisphere and Southern Hemisphere temperature extremes by identifying the percentage of ensemble members showing decadal average temperatures more than one standard deviation above or below the 1000–2000 baseline (Fig. 3). Extended periods where at least 33% of the reconstruction ensemble members in both hemispheres simultaneously show extreme cold or warm temperatures are identified only between 1594 and 1677 and since 1967, respectively. Since 1974 more than 66%, and since 1979 more than 90%, of ensemble members show synchronous positive extremes (corresponding to ‘likely’ and ‘very likely’ categories using IPCC AR5 calibrated uncertainty classification). This analysis provides evidence for a global cold phase coinciding with the peak of the Northern Hemisphere ‘Little Ice Age’ (LIA) and a late-twentieth century warm phase of unprecedented duration and magnitude within the past 1000 years. In contrast, we find no empirical support for a globally coherent ‘Medieval Climate Anomaly’ (MCA) at decadal timescales during the past millennium14. Our new temperature reconstruction from the Southern Hemisphere suggests that data from the Northern Hemisphere alone are insufficient to characterize global scale temperature anomalies, trends and extremes.

Simulated extreme conditions shown in Fig. 3 are a direct expression of external forcing (Fig. 3d). The notable reconstructed seventeenth-century peak LIA is less prominent in the model ensemble, which shows the clearest global cooling signal in response to volcanic eruptions around 1815 (Tambora), the 1450s (Kuwae) and 1258 (Samalas). External climate forcing as incorporated in the current climate model simulations does not account for key features of reconstructed temperature variation. This suggests that internal variability was a key driver for hemispheric and global decadal-scale extreme periods.

To further investigate inter-hemispheric temperature coherence, we calculate the ten-year running temperature differences between the standardized Northern Hemisphere and Southern Hemisphere reconstructions (Fig. 4a). The variability and amplitude of the Northern Hemisphere–Southern Hemisphere temperature difference fluctuates considerably over time, showing periods with large divergence (for example, around 1100 and 1575) and with more in-phase variability (for example, the thirteenth and eighteenth centuries). The distinct and internally driven drop in Northern Hemisphere temperatures around 19702 was preceded by several other analogous periods of contrasting hemispheric temperature trends. Internal ocean–atmosphere processes appear to be the main driver of the larger Northern Hemisphere–Southern Hemisphere differences; only two episodes of contrasting temperature regimes coincide with strong volcanic eruptions (Kuwae and Tambora). Model simulations also contain periods of contrasting inter-hemispheric temperature trends, but with notably smaller differences between the hemispheres (Supplementary Figs 36–59): median reconstructed Northern Hemisphere–Southern Hemisphere differences are outside the 10th–90th percentile range of model simulations 42% of the time (Fig. 4). The lower Northern Hemisphere–Southern Hemisphere temperature contrasts within the simulations are not only evident in the pre-instrumental period but also during the twentieth century3 (Fig. 4b, c), when both the reconstructions and instrumental data2 show strong inter-hemispheric variability.

Figure 4: Inter-hemispheric temperature difference.

a, Difference between 10-year filtered Northern Hemisphere–Southern Hemisphere temperatures in the ensemble reconstructions after detrending and standardizing (black). The solid line represents the ensemble median, grey shading the percentiles. Cyan shows the instrumental data 1880–201028. Red lines are the 10th and 90th percentiles from the ensemble of model simulations. Volcanic forcing29 shown at the top in brown. b, Ensemble distribution of the reconstructed absolute Northern Hemisphere–Southern Hemisphere temperature difference averaged over the 1000–1900 period. Red boxplot represents model simulations. c as b but for the twentieth century, cyan represents instrumental data.

The Southern Hemisphere reconstruction presented here allows new insights into the characteristics of the global climate system. For example, it has been proposed that the Southern Hemisphere response to external forcing may be delayed and buffered by the large heat capacity of the oceans17, 18. The greater amplitude of pre-industrial temperature variation in the Northern Hemisphere (0.67 °C ± 0.46 °C (2σ ensemble spread) versus 0.37 °C ± 0.11 °C in the Southern Hemisphere), the approximately two-century Northern Hemisphere lead during medieval times and the approximately 25 year lead during the era of industrial warming are in line with this hypothesis. However, we find no evidence for a consistent lag between Northern Hemisphere and Southern Hemisphere temperatures (Supplementary Section 8). The coherent and extreme cool conditions in both hemispheres around 1600 are unique within the past millennium and now offer perhaps the most viable explanation for the drop in global CO2 (difference of 8.37 ppm or 0.19 W m−2 between 1540–1580 and 1600–16405, 19, 20; Fig. 3d), which may not be sufficiently explained by land use change21 or Northern Hemisphere-temperature–CO2 feedbacks5.

Our results suggest that large, internally driven temperature contrasts between the hemispheres, such as identified in the twentieth century2 have repeatedly occurred on the policy-relevant multi-decadal to centennial timescales. This finding is strengthened by evidence from annually resolved regional temperature reconstructions14, 22, 23 and the timing of glacial fluctuations in New Zealand and the Northern Hemisphere24. Our data support hypotheses that global and hemispheric temperature extremes and transitions may be initiated11, 16, 25 and prolonged26 by internal variability and feedbacks. Analyses targeting periods where climate models and reconstructions differ will be necessary to identify weaknesses in both proxy- and model-based representations of the Earth’s climate system. However, the strong inter-hemispheric coupling in the simulations assessed herein suggests that models overestimate the strength of externally forced relative to internal climate system variability, therefore implying more limited predictability not only on regional1, 27 but also hemispheric scales. The stronger coherence between the Northern Hemisphere temperature reconstructions and external forcings similarly implies that detection and attribution studies10 and climate sensitivity estimates5, 6 based on Northern Hemisphere data alone may not be representative of the global climate system. Future consideration of Southern Hemisphere temperature evolution should reduce uncertainties in estimating and attributing natural and anthropogenically forced climate variations.

Southern Hemisphere reconstruction ensemble.

We use the Southern Hemisphere spatial mean of the Goddard Institute for Space Studies (GISS) Surface Temperature Analysis (GISTEMP) temperature grid28 as the instrumental predictand for the reconstruction. The palaeoclimate data network15 consists of 48 marine (46 coral and 2 sediment time series) and 277 terrestrial (206 tree-ring sites, 42 ice core, 19 documentary, 8 lake sediment and 2 speleothem) records (details in Supplementary Section 1). Although proxy records are preferentially located towards land areas, the network represents a considerable improvement of both geographical coverage and proxy quantity and quality (for example, resolution, length) since the last Southern Hemisphere reconstruction effort4. Proxies are screened with local grid-cell temperatures28 yielding 111 temperature predictors (Fig. 1) for the nested multivariate principal component regression procedure23. A 3,000-member ensemble reconstruction of annual Southern Hemisphere temperatures over the period 1000–2000 was generated with the spread of ensemble members considered a measure of uncertainty.

For each ensemble member we use different reconstruction parameters by randomly selecting a subset of proxies, as well as varying the calibration/verification intervals within 1911–1990, and other reconstruction parameters (details in Supplementary Section 2.2). The perturbation of calibration/verification periods allows a ‘verification ensemble mean’ to be calculated over the 1911–1990 period by averaging all members where a given year was used for verification (and not for calibration). Analogously, a ‘calibration ensemble mean’ was calculated. These time series and their corresponding Reduction of Error (RE) skills are shown in Fig. 1c, b, respectively. These statistics along with additional verification based on the sparse early Southern Hemisphere instrumental data (RE = 0.41–0.90; Supplementary Fig. 10) point to reconstructive skill over the past millennium. In addition to traditional reconstruction uncertainty estimates based on regression residuals, we assess the influence of the ensemble perturbations on the reconstruction outcome. Uncertainty envelopes in Fig. 2a represent combined calibration and ensemble uncertainties (details inSupplementary Section 2.4).

Although we have taken steps to provide robust results considering the challenges of proxy-based reconstructions (for example, potential underestimation of past climate amplitudes) discussed in the literature, we note that all reconstruction approaches contain uncertainties. The fact that our reconstruction verifies well and captures interannual and decadal-scale temperature fluctuations during the instrumental period (Fig. 1 and Supplementary Section 3) indicates reduced probability of such artefacts. An extensive assessment of reconstruction robustness is provided inSupplementary Section 3.2 and Supplementary Figs 13–26, with tests demonstrating that the potential bias introduced by the proxy-screening and reconstruction methods or by single dominant records or proxy archives is small.

Northern Hemisphere reconstruction ensemble.

Details concerning the Northern Hemisphere reconstructions are provided in ref. 5 andSupplementary Section 5. The most important difference from our Southern Hemisphere reconstruction is that it is not based on a single predictor matrix but uses nine published Northern Hemisphere reconstructions based on different (but not independent) proxy sets and various reconstruction methodologies. In ref. 5, the individual single-member reconstructions were recalibrated to instrumental temperature data using different calibration periods as ensemble parameters, resulting in a total of 521 ensemble members. The Northern Hemisphere ensemble spread is larger than in the Southern Hemisphere owing to the relatively large differences between some of the original sub-reconstructions and the composite-plus-scaling approach over a range of time windows in ref. 5. To best illustrate these two approaches, the ensemble means of the nine sub-reconstructions are shown for the Northern Hemisphere in Fig. 2a. As a consequence of these methodological differences and the larger ensemble spread in the Northern Hemisphere, one would expect generally reduced probabilities for extreme periods in the Northern Hemisphere. However,Fig. 3a, b shows similar fractions of periods with high probabilities for extremes, indicating a similar consistency between ensemble members in the timing of extreme periods in both hemispheres.